PicnicHealth (S14)

PicnicHealth makes medical records useful for patients, doctors, and researchers.

Machine Learning Engineer

$0 - $00.00% - 0.00%

Location
 
San Francisco, CA
Job Type
 
Full-time
Experience
 
3+ years
About PicnicHealth

Picnic’s mission is to structure the world’s medical data to make it useful. We work directly with patients to collect, digitize, and manage their complete medical records, giving them with control over their care through a personal health timeline (demo.picnichealth.com). We also partner with biopharma companies (3 of the top 6 in the world) who sponsor PicnicHealth accounts for research volunteers. Through this work we’re building the data sets that power some of today’s most cutting edge medical research. We’re currently 40 people based in the Mission District of SF, nearing our Series B raise, and continuing to grow!

About the role

Skills: Python, TensorFlow, Machine Learning, Deep Learning, Natural Language Processing, Image Processing, Keras, PostgreSQL

Full Job Posting

Picnic’s mission is to structure the world’s medical data to make it useful. We work directly with patients to collect, digitize ,and manage their complete medical records, giving them with control over their care through a personal health timeline. We also partner with biotech, genomics, and pharma companies who sponsor PicnicHealth accounts for research volunteers. Through this work we’re building the data sets that power some of today’s most cutting edge medical research.

ML at Picnic Machine learning is at the heart of our work. While the healthcare industry is waiting for standards and APIs to take hold, we’re able to create meaningful medical data today through our process for extracting and structuring medical information from records in whatever format they exist in the real world. We ingest medical records (faxes, scans, etc of printouts from EHRs, electronic data from EHRs) and convert them into structured, labeled medical data. Think of what we do as a multi-stage, human-in-the-loop machine learning system. We 1) run OCR to transform the image into text, 2) identify and label regions of the record, and 3) classify medical concepts with codes from standard ontologies (SNOMED CT, LOINC, RxNorm, ICD, etc) and structure relevant attributes. Ultimately, structuring data is just the starting point. We’ll use machine learning to pull insights from medical data and surface the most relevant information to make better decisions around care.

We’ve sourced and trained a scalable team of nurses in the Philippines to identify and label data and have already labeled records from more than 15,000 different doctors. We’re going through a crazy period of 20x growth this year, coming off our recent Grand Prize finish in Google Cloud’s Machine Learning Startup Competition.

The Role As one of our first dedicated machine learning engineers, you’ll take ownership over our machine learning efforts. We need you to not only build out and deploy models, but also establish best practices, mentor team members, and bring expertise to how we think about machine learning.

Responsibilities:

  • Develop machine learning models to improve PicnicHealth’s product and processing efficiency
  • Apply expert software development skills to build intelligent user experiences leveraging machine learning
  • Own the machine learning pipeline — systems for training, versioning, deploying, and testing models
  • Work with product, operations, and sales teams to help define use cases, and develop methodology and benchmarks to evaluate different machine learning approaches

A candidate must have:

  • BA/BS degree in Computer Science, related technical field or equivalent practical experience
  • Experience with linear algebra, calculus and statistics
  • Shipped code for 3+ years
  • Leveraged machine learning in production environments

An ideal candidate has:

  • An MS or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, or related technical field
  • Exposure to industry or academic research
  • Experience with Python, and Python machine learning tooling, including TensorFlow
  • Exposure to Deep Learning, Gradient Boosting Machines, and other supervised classification methods
  • Large data analysis and visualization experience
  • Experience building web applications
  • Desire to kick ass and save lives

Apply here

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